activity
20182022
most citedTJU-DHD: A Diverse High-Resolution Dataset for Object Detection

89 citations · 140 across the 7 of their papers we have counts for

collaborators

10 papers

cs.CV2022

PSTR: End-to-End One-Step Person Search With Transformers

Jiale Cao, Yanwei Pang, Rao Muhammad Anwer +4

We propose a novel one-step transformer-based person search framework, PSTR, that jointly performs person detection and re-identification (re-id) in a single architecture. PSTR com…

cs.CV20222 cited

Video Instance Segmentation via Multi-scale Spatio-temporal Split Attention Transformer

Omkar Thawakar, Sanath Narayan, Jiale Cao +6

State-of-the-art transformer-based video instance segmentation (VIS) approaches typically utilize either single-scale spatio-temporal features or per-frame multi-scale features dur…

cs.CV20211 cited

Shape Prior Non-Uniform Sampling Guided Real-time Stereo 3D Object Detection

Aqi Gao, Jiale Cao, Yanwei Pang

Pseudo-LiDAR based 3D object detectors have gained popularity due to their high accuracy. However, these methods need dense depth supervision and suffer from inferior speed. To sol…

cs.CV202112 cited

Track to Detect and Segment: An Online Multi-Object Tracker

Jialian Wu, Jiale Cao, Liangchen Song +3

Most online multi-object trackers perform object detection stand-alone in a neural net without any input from tracking. In this paper, we present a new online joint detection and t…

cs.CV2020

Co-mining: Self-Supervised Learning for Sparsely Annotated Object Detection

Tiancai Wang, Tong Yang, Jiale Cao +1

Object detectors usually achieve promising results with the supervision of complete instance annotations. However, their performance is far from satisfactory with sparse instance a…

cs.CV202089 cited

TJU-DHD: A Diverse High-Resolution Dataset for Object Detection

Yanwei Pang, Jiale Cao, Yazhao Li +3

Vehicles, pedestrians, and riders are the most important and interesting objects for the perception modules of self-driving vehicles and video surveillance. However, the state-of-t…